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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Jurnal Penelitian dan Pendidikan IPS Nusantara of Research : Jurnal Hasil-hasil penelitian Universitas Nusantara PGRI Kediri (e-journal) Psikopedagogia SMATIKA Indonesian Journal of Guidance and Counseling: Theory and Application Jurnal Bimbingan dan Konseling Terapan Satya Widya JURNAL KONSELING GUSJIGANG Network Engineering Research Operation [NERO] JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI International Journal of Research in Counseling and Education Jurnal Basicedu Psikologi Konseling: Jurnal Kajian Psikologi dan Konseling Genta Mulia : Jurnal Ilmiah Pendidikan EduPsyCouns: Journal of Education, Psychology and Counseling Jurnal Pengabdian Masyarakat Asia Charity : Jurnal Pengabdian Masyarakat International Journal of Community Service PELS (Procedia of Engineering and Life Science) Indonesian Journal Of Educational Research and Review Jurnal Basicedu eProceedings of Engineering Jurnal Pengabdian Masyarakat Bangsa Kelola: Jurnal Manajemen Pendidikan BATIK: Jurnal Pengembangan dan Pengabdian Masyarakat Multikultural
Setyorini Setyorini
Institut Teknologi Dan Bisnis Asia Malang
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Analysis of feature reduction for identifying stress levels electroencephalogram signal based Setyorini, Setyorini; Zaeni, Ilham Ari Elbaith; Elmusyah, Hakkun
International Journal of Advances in Applied Sciences Vol 14, No 4: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i4.pp1137-1145

Abstract

Stress identification based on electroencephalogram (EEG) signals has become a rapidly growing research topic, with the main approaches utilizing features from the frequency domain and time-frequency domain. This research aims to combine principal component analysis (PCA) and independent component analysis (ICA) for feature extraction to improve the accuracy of stress identification. Additionally, PCA+ICA features are reduced from 64 to 32 columns to optimize computational efficiency without losing important information from the EEG signal. The stress identification models used in this research include Ensemble, naive Bayes, and support vector machine (SVM). The data used are from the SAM-40 task Stroop color trials 1, 2, and 3. Experimental results indicate that the combination of PCA+ICA features improves accuracy only in the ensemble method. Reducing PCA+ICA features from 64 to 32 columns led to an improvement in accuracy only for Stroop trial 2 data with the naive Bayes method.
Co-Authors Adriani Kalalembang Amatullah Karimah, Siti Ambarwati, Fajar Putri Anggita Intan Saputri Aqromi , Nur Lailatul Ari Eko Wibowo Bedy Purnama Danar Kurniawan, Karolus Derry Destian Didit Adytia Elmusyah, Hakkun Entik Insanudin Fadilla Cahyaningtyas Fajar Putri Ambarwati Fakhrurroja, Hanif Farah Afianti Firmansyah Arrozi, M Firosalia Kristin Fitrian, Farisa Dina Fransiska Sisilia Mukti Furqoon, Naufal Sayyid Galih Saputro, Mukhamad Rafi Galih Setiawan Hanif, Rifki Hanifan, Abdullah Hari Kurniawan, Hironimus Hironimus Hari Kurniawan Ike Kusdyah Rachmawati irsyada, abdulloh eizzi Ismail Ismail J.T. Lobby Loekmono, J.T. Lobby Jaenal Arifin Jaenal Arifin Jaenal Arifin Justita Dura Kala'lembang, Adriani Khairi, Alfin Mifathul Khori Wahyu Kristina, Ayu Dina Kurniawan, Hironimus Hari Kurniawan, Karolus Danar Kusnarto Kurniawan Labib, Fahdi Lailatu Aqromi , Nur Layli Dwi Rohmatunnisa mulyaningtyas, mulyaningtyas Nila Zaimatus Septiana, Nila Zaimatus Nopendri Nopendri Novita Sari Nur Lailatul Aqromi Nurul Afiyah, Siti Puji Subekti Purnomo, Andreas Wisnu Adi Purwoko, Agus Puspa Dewi, Mariana Rahayu, Dwi Sri Ratnawati Ratnawati Rendy Munadi Ria Fitriani Rina Dewi Indahsari Rizqi Nur Astuti Nur Astuti Samsul Arifin Seno Adi Putra Siti Nurul Afiyah Siti Nurul Afiyah Tatang Mulyana Tien Fabrianti Kusumasari Titania Dwi Andini Tritjahjo Danny Soesilo Umbu Tagela Wa Ode Irma Sari Wahyu Rizky Wibowo Widianto Soekarnen Widyanto, Toto Wongarso, Silviana Winty Yahya Adi Setyawan Yari Dwikurnaningsih Yayi Suryo Prabandari Yosua Ivan Pradana Yuggo Afrianto Zaeni, Ilham Ari Elbaith Zulfikar Ali